Consumer Finance Solution_Industry Solutions_Solutions_Shanghai XK Digital Technology Co., Ltd.

Problems And Challenges

Acquisition Of High-Quality Data

Consumer finance credit products require a large amount of customer data support, but traditional data collection methods have problems such as low data quality and single data sources, which cannot accurately reflect the true situation of customers.
Application Of New Technology

Mining big data requires the application of advanced technology and rich industry experience, which requires a lot of manpower and financial investment.
Marketing Management

Financial institutions face issues such as high marketing costs and low conversion rates. The challenge is to achieve accurate marketing, reduce marketing costs, and increase conversion rates.

Solution

Data Acquisition And Processing

Using multidimensional data acquisition methods, including traditional data, third-party data, and behavioral data, combined with data cleaning and preprocessing technology, to ensure the accuracy and completeness of the data, thereby improving the accuracy of risk control and marketing decisions.
Risk Assessment Model

Based on big data technology, a multidimensional, real-time risk assessment model is constructed, which not only evaluates customers' personal information and credit status but also monitors their behavioral characteristics, identifies potential risks, and realizes dynamic risk control strategies and risk warnings.
Precision Marketing Management

Using big data technology, customer portraits are established to accurately identify customer needs and behavior and use personalized and scenario-based marketing methods, such as personalized recommendations and intelligent customer service, to enhance customer experience and conversion rates. At the same time, a comprehensive and real-time compliance monitoring system is constructed to monitor compliance in product marketing and transaction processes, timely detect and correct violations, and ensure the company's compliance and risk control.

Customer Case

Customer: Mr. Li, 30 years old, has a stable job, and a monthly income of 8,000 yuan. He plans to buy a new car but needs a loan because he does not have enough cash.

Solution:

Credit risk assessment: Using big data technology and risk control models to analyze his social network, online activities, purchase history, and other data for credit risk assessment. Data sources can be obtained from third-party data providers. If Mr. Li's credit risk is low, more competitive loan rates can be offered to him.

Consumption demand assessment: Through analysis of his purchase history and browsing behavior, his consumption preferences and needs can be understood.

Intelligent risk control: Using machine learning and artificial intelligence technologies, intelligent risk control can be applied to Mr. Li's loan application. These technologies can analyze a large amount of data, including Mr. Li's personal information, loan history, financial situation, etc. If there is any risk, it can be intercepted in time.

Customized precision marketing: Through analyzing Mr. Li's data, his consumption habits, interests, purchasing power, etc. can be understood, and personalized marketing can be applied to him. For example, suitable cars, car insurance, loan plans, etc. can be recommended to him.